A relationship between gill silver accumulation and acute silver toxicity in the freshwater rainbow trout: Support for the acute silver biotic ligand model
Bibliographic record
Abstract
Rainbow trout were exposed to a range of silver concentrations (as AgNO3) in flowing synthetic soft water (0.05 mM Na+, 0.05 mM Cl-, 0.05 mM Ca2+, 0.02 mM Mg2+, 0.02 mM K+, pH 7.0, approximately 0.7 mg C/L dissolved organic carbon, 10 mg CaCO3/L, 10 +/- 2 degrees C) to investigate a possible relationship between short-term gill silver accumulation (3 h or 24 h) and acute silver toxicity (96-h mortality). We also investigated potential relationships between gill silver accumulation and inhibition of Na+ uptake plus inhibition of gill Na+K(+)-adenosine triphosphatase (ATPase) activity. The 96-h median lethal concentration (LC50) values were 13.3 microg total Ag L(-1) and 3.3 microg dissolved Ag L(-1). A relationship was demonstrated between 3-h and 24-h gill silver accumulation and 96-h mortality. A relationship also was demonstrated between gill silver accumulation and inhibition of Na+ uptake at 24 h of exposure. No relationship between gill silver accumulation and inhibition of gill Na+K(+)-ATPase activity was found. The 96-h median lethal gill accumulation (LA50) values of 129 (at 3 h) and 191 ng g(-1) (at 24 h) and a conditional equilibrium binding constant of 8.0 for Ag+ binding to the gills were calculated. These observations support use of the silver biotic ligand model (BLM) as a regulatory tool to predict acute silver toxicity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".